Abstract
Despite the remarkable improvement of hardware and network technology, the inevitable delay from a user's command action to a system response is still one of the most crucial influence factors in user experiences (UXs). Especially for a web video service, an initial delay from click action to video start has significant influences on the quality of experience (QoE). The initial delay of a system can be minimized by preparing execution based on predicted user's intention prior to actual command action. The introduction of the sequential and concurrent flow of resources in human cognition and behavior can significantly improve the accuracy and preparation time for intention prediction. This paper introduces a threaded interaction model and applies it to user intention prediction for initial delay reduction in web video access. The proposed technique consists of a candidate selection module, a decision module and a preparation module that prefetches and preloads the web video data before a user's click action. The candidate selection module selects candidates in the web page using proximity calculation around a cursor. Meanwhile, the decision module computes the possibility of actual click action based on the cursor-gaze relationship. The preparation activates the prefetching for the selected candidates when the click possibility exceeds a certain limit in the decision module. Experimental results show a 92% hit-ratio, 0.5-s initial delay on average and 1.5-s worst initial delay, which is much less than a user's tolerable limit in web video access, demonstrating significant improvement of accuracy and advance time in intention prediction by introducing the proposed threaded interaction model.
Highlights
In spite of remarkable hardware and network speed improvement, unavoidable delay from a user input action to a system response still exists, and it causes significant adverse effects on the system usability and user experiences (UXs)
The overall performance measure of the proposed prefetching technique is the initial delay that is defined as the time period from the moment of the target click to the moment a video playing
The design parameters and performance evaluation parameters obtained from 24 participants were analyzed to set the design guidelines for further research in user intention prediction for prefetching in web access
Summary
In spite of remarkable hardware and network speed improvement, unavoidable delay from a user input action to a system response still exists, and it causes significant adverse effects on the system usability and user experiences (UXs). Various target prediction schemes based on movement vector analysis [15], the neural network algorithm [16], the Kalman filter algorithm [16,17], the kinematic template matching algorithm [18] and area cursor techniques [19,20,21,22] have been proposed to improve the target selection task They are not suitable for current web applications due to the complicated layout of hyperlinks and the excessive computational consumptions. These gaze-only intention prediction techniques are very advantageous to identify the context, propensity and preference of the user They are not suitable for the web video prefetching application, because the early studies focused on the contextual and implicit intention about the user activity rather than the behavioral and explicit intention to click a target among chosen candidates.
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